In a media storage system, many media drives interact with many types of media. If an interaction results in a defective performance, then it can be difficult to determine the culprit of the problem. In some cases, a process of elimination may be employed where either the media could be mounted in another media drive or another media with a good performance record could be mounted in the media drive. A repeated failure would indicate the faulty component. However, this process of elimination may be time-consuming and unrealistic.
In current media storage systems, there may be several media drives with thousands or more media capable of being loaded into these media drives. The interaction experience between the various media drives and media can range from a great experience all the way to a non-existent experience. On the lower end of the performance spectrum, the negative experiences may involve lower throughput of data or no data at all.
A media drive is capable of performing certain actions to compensate for any problems it is experiencing in an interaction with a media. As a result, the media drive may hide many problems. However, over time, it is still likely that the media drive will exhibit symptoms of the below-average experience between the media drive and the media.
In this light, it would be beneficial to provide a system where it can be predicted if certain components, such as a media drive or a media itself, will have a problem. In this way, certain actions may be taken that could prevent the problem before it ever occurs. For instance, if a media is predicted to provide continual worsening experiences through its lifetime, then it would be prudent to replace this media before these experiences actually occur. A mechanism to help accurately predict and prevent impending media drive or media degradation and failure at customer sites would be beneficial.